1. Field of Invention
The present invention generally relates to biometric identification using blood vessel images. More specifically, the present invention relates to the use of hierarchical feature indexing for quick vein recognition
2. Description of Related Art
Biometrics refers to the use of intrinsic human traits for personal identification purposes. That is, a person may be identified by one or a combination of multiple different personal trait characteristics of that person. Examples of such personal traits are a fingerprint, a hand print (length and thickness of the fingers, size of the hand itself), a retina scan (pattern of blood vessels in the eye), an iris scan, a facial photograph, a blood vessel pattern (vein pattern), a voice print, a dynamic signature (the shape and time pattern for writing a signature), or a keystroke pattern (key entry timing).
Of particular interest are biometric identification techniques that use blood vessels, or veins, for personal identification. A method for automatically identifying blood vessels in a diagnostic image is described in U.S. Pat. No. 7,343,032, and an example of a technique for obtaining diagnostic images of blood vessels from a human eye for personal identification (ID) purposes is shown in U.S. Pat. No. 6,569,104. Another example provided in U.S. Pub. No. 2010/0045788 describes the use of visible and near infrared light to acquire diagnostic images of a palm print image for personal identification. A technique for using vein authentication on a finger for identification purposes is described in U.S. Pub. No. 2010/0198078.
Various techniques are known for identifying specific pattern structures in diagnostic images. One technique for identifying blood vessel patterns is by means of path-based tree matching, such as described in U.S. Pat. No. 7,646,903. Tree matching algorithms require tree structures as input. This structure describes the tree as a series of branches interconnected through branch points. Several known algorithms can be used to obtain the tree structure including tracking, segmentation, and skeletonization. Once the tree structure is obtained, a matching algorithm operates directly on the structure and any data contained therein.
There are various matching algorithms known in the art, but they tend to be slow and computationally intensive. What is needed is an efficient method of applying tree matching to biometric applications.
Another object of the present invention is to provide a hierarchical approach that not only identifies the closest matching vein pattern to a query, but also has the ability to reliability and efficiently reject a false positive identification.